Optimal encoding rules for synthetic genes: the need for a community effort

Assessing optimal: inequalities in codon optimization algorithms

BACKGROUND

Custom genes have become a common resource in recombinant biology over the last 20 years due to the plummeting cost of DNA synthesis. These genes are often "optimized" to non-native sequences for overexpression in a non-native host by substituting synonymous codons within the coding DNA sequence (CDS). A handful of studies have compared native and optimized CDSs, reporting different levels of soluble product due to the accumulation of misfolded aggregates, variable activity of enzymes, and (at least one report of) a change in substrate specificity. No study, to the best of our knowledge, has performed a practical comparison of CDSs generated from different codon optimization algorithms or reported the corresponding protein yields.

RESULTS

In our efforts to understand what factors constitute an optimized CDS, we identified that there is little consensus among codon-optimization algorithms, a roughly equivalent chance that an algorithm-optimized CDS will increase or diminish recombinant yields as compared to the native DNA, a near ubiquitous use of a codon database that was last updated in 2007, and a high variability of output CDSs by some algorithms. We present a case study, using KRas4B, to demonstrate that a median codon frequency may be a better predictor of soluble yields than the more commonly utilized CAI metric.

CONCLUSIONS

We present a method for visualizing, analyzing, and comparing algorithm-optimized DNA sequences for recombinant protein expression. We encourage researchers to consider if DNA optimization is right for their experiments, and work towards improving the reproducibility of published recombinant work by publishing non-native CDSs.

DNASynth: a computer program for assembly of artificial gene parts in decreasing temperature

Artificial gene synthesis requires consideration of nucleotide sequence development as well as long DNA molecule assembly protocols. The nucleotide sequence of the molecule must meet many conditions including particular preferences of the host organism for certain codons, avoidance of specific regulatory subsequences, and a lack of secondary structures that inhibit expression. The chemical synthesis of DNA molecule has limitations in terms of strand length; thus, the creation of artificial genes requires the assembly of long DNA molecules from shorter fragments. In the approach presented, the algorithm and the computer program address both tasks: developing the optimal nucleotide sequence to encode a given peptide for a given host organism and determining the long DNA assembly protocol. These tasks are closely connected; a change in codon usage may lead to changes in the optimal assembly protocol, and the lack of a simple assembly protocol may be addressed by changing the nucleotide sequence. The computer program presented in this study was tested with real data from an experiment in a wet biological laboratory to synthesize a peptide. The benefit of the presented algorithm and its application is the shorter time, compared to polymerase cycling assembly, needed to produce a ready synthetic gene.

Genome-scale analysis of translation elongation with a ribosome flow model

We describe the first large scale analysis of gene translation that is based on a model that takes into account the physical and dynamical nature of this process. The Ribosomal Flow Model (RFM) predicts fundamental features of the translation process, including translation rates, protein abundance levels, ribosomal densities and the relation between all these variables, better than alternative ('non-physical') approaches. In addition, we show that the RFM can be used for accurate inference of various other quantities including genes' initiation rates and translation costs. These quantities could not be inferred by previous predictors. We find that increasing the number of available ribosomes (or equivalently the initiation rate) increases the genomic translation rate and the mean ribosome density only up to a certain point, beyond which both saturate. Strikingly, assuming that the translation system is tuned to work at the pre-saturation point maximizes the predictive power of the model with respect to experimental data. This result suggests that in all organisms that were analyzed (from bacteria to Human), the global initiation rate is optimized to attain the pre-saturation point. The fact that similar results were not observed for heterologous genes indicates that this feature is under selection. Remarkably, the gap between the performance of the RFM and alternative predictors is strikingly large in the case of heterologous genes, testifying to the model's promising biotechnological value in predicting the abundance of heterologous proteins before expressing them in the desired host.

Manipulating the genetic code for membrane protein production: what have we learnt so far?

With synthetic gene services, molecular cloning is as easy as ordering a pizza. However choosing the right RNA code for efficient protein production is less straightforward, more akin to deciding on the pizza toppings. The possibility to choose synonymous codons in the gene sequence has ignited a discussion that dates back 50 years: Does synonymous codon use matter? Recent studies indicate that replacement of particular codons for synonymous codons can improve expression in homologous or heterologous hosts, however it is not always successful. Furthermore it is increasingly apparent that membrane protein biogenesis can be codon-sensitive. Single synonymous codon substitutions can influence mRNA stability, mRNA structure, translational initiation, translational elongation and even protein folding. Synonymous codon substitutions therefore need to be carefully evaluated when membrane proteins are engineered for higher production levels and further studies are needed to fully understand how to select the codons that are optimal for higher production. This article is part of a Special Issue entitled: Protein Folding in Membranes.

Gene optimization mechanisms: a multi-gene study reveals a high success rate of full-length human proteins expressed in Escherichia coli

The genetic code is universal, but recombinant protein expression in heterologous systems is often hampered by divergent codon usage. Here, we demonstrate that reprogramming by standardized multi-parameter gene optimization software and de novo gene synthesis is a suitable general strategy to improve heterologous protein expression. This study compares expression levels of 94 full-length human wt and sequence-optimized genes coding for pharmaceutically important proteins such as kinases and membrane proteins in E. coli. Fluorescence-based quantification revealed increased protein yields for 70% of in vivo expressed optimized genes compared to the wt DNA sequences and also resulted in increased amounts of protein that can be purified. The improvement in transgene expression correlated with higher mRNA levels in our analyzed examples. In all cases tested, expression levels using wt genes in tRNA-supplemented bacterial strains were outperformed by optimized genes expressed in non-supplemented host cells.

Multifactorial determinants of protein expression in prokaryotic open reading frames

A quantitative description of the relationship between protein expression levels and open reading frame (ORF) nucleotide sequences is important for understanding natural systems, designing synthetic systems, and optimizing heterologous expression. Codon identity, mRNA secondary structure, and nucleotide composition within ORFs markedly influence expression levels. Bioinformatic analysis of ORF sequences in 816 bacterial genomes revealed that these features show distinct regional trends. To investigate their effects on protein expression, we designed 285 synthetic genes and determined corresponding expression levels in vitro using Escherichia coli extracts. We developed a mathematical function, parameterized using this synthetic gene data set, which enables computation of protein expression levels from ORF nucleotide sequences. In addition to its practical application in the design of heterologous expression systems, this equation provides mechanistic insight into the factors that control translation efficiency. We found that expression is strongly dependent on the presence of high AU content and low secondary structure in the ORF 5' region. Choice of high-frequency codons contributes to a lesser extent. The 3' terminal AU content makes modest, but detectable contributions. We present a model for the effect of these factors on the three phases of ribosomal function: initiation, elongation, and termination.

Strategies for protein synthetic biology

Proteins are the most versatile among the various biological building blocks and a mature field of protein engineering has lead to many industrial and biomedical applications. But the strength of proteins—their versatility, dynamics and interactions—also complicates and hinders systems engineering. Therefore, the design of more sophisticated, multi-component protein systems appears to lag behind, in particular, when compared to the engineering of gene regulatory networks. Yet, synthetic biologists have started to tinker with the information flow through natural signaling networks or integrated protein switches. A successful strategy common to most of these experiments is their focus on modular interactions between protein domains or domains and peptide motifs. Such modular interaction swapping has rewired signaling in yeast, put mammalian cell morphology under the control of light, or increased the flux through a synthetic metabolic pathway. Based on this experience, we outline an engineering framework for the connection of reusable protein interaction devices into self-sufficient circuits. Such a framework should help to ‘refacture’ protein complexity into well-defined exchangeable devices for predictive engineering. We review the foundations and initial success stories of protein synthetic biology and discuss the challenges and promises on the way from protein- to protein systems design.

Codon optimization enhances protein expression of human peptide deformylase in E. coli

Human peptide deformylase (hPDF), located in the mitochondria, has recently become a promising target for anti-cancer therapy. However, the expression of the hPDF gene in Escherichia coli is not efficient likely due to extremely high levels of GC content as well as the presence of rare codons. We performed codon optimization of the hPDF gene in order to reduce GC content and to eliminate rare codons. Putative stable secondary structures of the optimized gene were also reduced. Codon optimization increased the expression of hPDF protein (residues 63-243) presumably by reducing the GC content. A large amount of soluble hPDF was obtained upon its fusion with thioredoxin (Trx-hPDF), although an insoluble fraction was still dominant. We confirmed that Co(2+) is an optimal metal for increasing the activity of purified Trx-hPDF, and that actinonin acts as an efficient inhibitor. Therefore, a large amount of purified hPDF protein would provide many benefits for the screening of various drug candidates.

Design parameters to control synthetic gene expression in Escherichia coli

BACKGROUND

Production of proteins as therapeutic agents, research reagents and molecular tools frequently depends on expression in heterologous hosts. Synthetic genes are increasingly used for protein production because sequence information is easier to obtain than the corresponding physical DNA. Protein-coding sequences are commonly re-designed to enhance expression, but there are no experimentally supported design principles.

PRINCIPAL FINDINGS

To identify sequence features that affect protein expression we synthesized and expressed in E. coli two sets of 40 genes encoding two commercially valuable proteins, a DNA polymerase and a single chain antibody. Genes differing only in synonymous codon usage expressed protein at levels ranging from undetectable to 30% of cellular protein. Using partial least squares regression we tested the correlation of protein production levels with parameters that have been reported to affect expression. We found that the amount of protein produced in E. coli was strongly dependent on the codons used to encode a subset of amino acids. Favorable codons were predominantly those read by tRNAs that are most highly charged during amino acid starvation, not codons that are most abundant in highly expressed E. coli proteins. Finally we confirmed the validity of our models by designing, synthesizing and testing new genes using codon biases predicted to perform well.

CONCLUSION

The systematic analysis of gene design parameters shown in this study has allowed us to identify codon usage within a gene as a critical determinant of achievable protein expression levels in E. coli. We propose a biochemical basis for this, as well as design algorithms to ensure high protein production from synthetic genes. Replication of this methodology should allow similar design algorithms to be empirically derived for any expression system.

Plasmid DNA vaccine vector design: impact on efficacy, safety and upstream production

Critical molecular and cellular biological factors impacting design of licensable DNA vaccine vectors that combine high yield and integrity during bacterial production with increased expression in mammalian cells are reviewed. Food and Drug Administration (FDA), World Health Organization (WHO) and European Medical Agencies (EMEA) regulatory guidance's are discussed, as they relate to vector design and plasmid fermentation. While all new vectors will require extensive preclinical testing to validate safety and performance prior to clinical use, regulatory testing burden for follow-on products can be reduced by combining carefully designed synthetic genes with existing validated vector backbones. A flowchart for creation of new synthetic genes, combining rationale design with bioinformatics, is presented. The biology of plasmid replication is reviewed, and process engineering strategies that reduce metabolic burden discussed. Utilizing recently developed low metabolic burden seed stock and fermentation strategies, optimized vectors can now be manufactured in high yields exceeding 2 g/L, with specific plasmid yields of 5% total dry cell weight.

Combined protein construct and synthetic gene engineering for heterologous protein expression and crystallization using Gene Composer

Background

With the goal of improving yield and success rates of heterologous protein production for structural studies we have developed the database and algorithm software package Gene Composer. This freely available electronic tool facilitates the information-rich design of protein constructs and their engineered synthetic gene sequences, as detailed in the accompanying manuscript.

Results

In this report, we compare heterologous protein expression levels from native sequences to that of codon engineered synthetic gene constructs designed by Gene Composer. A test set of proteins including a human kinase (P38α), viral polymerase (HCV NS5B), and bacterial structural protein (FtsZ) were expressed in both E. coli and a cell-free wheat germ translation system. We also compare the protein expression levels in E. coli for a set of 11 different proteins with greatly varied G:C content and codon bias.

Conclusion

The results consistently demonstrate that protein yields from codon engineered Gene Composer designs are as good as or better than those achieved from the synonymous native genes. Moreover, structure guided N- and C-terminal deletion constructs designed with the aid of Gene Composer can lead to greater success in gene to structure work as exemplified by the X-ray crystallographic structure determination of FtsZ from Bacillus subtilis. These results validate the Gene Composer algorithms, and suggest that using a combination of synthetic gene and protein construct engineering tools can improve the economics of gene to structure research.

You're one in a googol: optimizing genes for protein expression

A vast number of different nucleic acid sequences can all be translated by the genetic code into the same amino acid sequence. These sequences are not all equally useful however; the exact sequence chosen can have profound effects on the expression of the encoded protein. Despite the importance of protein-coding sequences, there has been little systematic study to identify parameters that affect expression. This is probably because protein expression has largely been tackled on an ad hoc basis in many independent projects: once a sequence has been obtained that yields adequate expression for that project, there is little incentive to continue work on the problem. Synthetic biology may now provide the impetus to transform protein expression folklore into design principles, so that DNA sequences may easily be designed to express any protein in any system. In this review, we offer a brief survey of the literature, outline the major challenges in interpreting existing data and constructing robust design algorithms, and propose a way to proceed towards the goal of rational sequence engineering.

Experimental analysis of gene assembly with TopDown one-step real-time gene synthesis

Herein we present a simple, cost-effective TopDown (TD) gene synthesis method that eliminates the interference between the polymerase chain reactions (PCR) assembly and amplification in one-step gene synthesis. The method involves two key steps: (i) design of outer primers and assembly oligonucleotide set with a melting temperature difference of >10°C and (ii) utilization of annealing temperatures to selectively control the efficiencies of oligonucleotide assembly and full-length template amplification. In addition, we have combined the proposed method with real-time PCR to analyze the step-wise efficiency and the kinetics of the gene synthesis process. Gel electrophoresis results are compared with real-time fluorescence signals to investigate the effects of oligonucleotide concentration, outer primer concentration, stringency of annealing temperature, and number of PCR cycles. Analysis of the experimental results has led to insights into the gene synthesis process. We further discuss the conditions for preventing the formation of spurious DNA products. The TD real-time gene synthesis method provides a simple and efficient method for assembling fairly long DNA sequence, and aids in optimizing gene synthesis conditions. To our knowledge, this is the first report that utilizes real-time PCR for gene synthesis.